CeO2–ZnO catalyst

i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 3 7 ( 2 0 1 2 ) 4 7 4 9 e4 7 6 1

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Applying a face-centered central composite design to optimize the preferential CO oxidation over a PtAu/CeO2eZnO catalyst Sangobtip Pongstabodee a,c,*, Sutarawadee Monyanon a, Apanee Luengnaruemitchai b,c a

Department of Chemical Technology, Faculty of Science, Chulalongkorn University, 254 Phayathai Road, Patumwan, Bangkok 10330, Thailand b The Petroleum and Petrochemical College, Chulalongkorn University, 254 Phayathai Road, Patumwan, Bangkok 10330, Thailand c Center for Petroleum, Petrochemicals and Advanced Materials, Chulalongkorn University, 254 Phayathai Road, Patumwan, Bangkok 10330, Thailand

article info

abstract

Article history:

The catalytic performance for the preferential oxidation of CO over a 1% (w/w) PtAu/

Received 11 October 2011

CeO2eZnO catalyst prepared by co-precipitation was investigated using a full 2k factorial

Received in revised form

design with three central points and a 95% confidence interval, in order to screen for the

24 November 2011

importance of the operating temperature (
C) and the H2O and CO2 contents (%) in the

Accepted 4 December 2011

simulated reformate gas on the CO conversion and selectivity. The catalyst was charac-

Available online 3 January 2012

terized by TEM, BET, XRD and FTIR. The temperature and CO2 content had a significant influence on the conversion, whilst the selectivity depended on the temperature only. A

Keywords:

face-centered central composite design was then used to evaluate the optimal conditions

H2O and CO2 content

by simultaneously considering the maximal conversion, selectivity and constraints of the

Preferential oxidation of CO

composition of realistic reformate gas. The difference in the estimated response and the

Statistical design of experiment

experimental one was within 2% and 3% for routing simulated and realistic reformate

Face-centered

gases, respectively.

central

composite

Copyright ª 2011, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights

design

reserved.

1.

Introduction

Hydrogen is an environmentally friendly fuel of potentially widespread use, especially for proton exchange membrane fuel cells (PEMFCs), which are one of the candidate energy sources for portable power appliances and powering vehicles. Nevertheless, the requirement of pure hydrogen for PEMFCs and the issue of the safety of a large capacity hydrogen storage system are the main limitations of hydrogen applications. Thus, recently considerable attention has focused upon producing hydrogen on-board directly. Such technology currently uses two major units, the hydrogen production unit

and the carbon monoxide (CO) elimination unit. A H2-rich stream can be obtained following catalytic conversion of methane, methanol, hydrocarbons or liquid fuels via steam reforming, partial oxidation or autothermal reforming. Of these substrates, methanol has received the most attention as a candidate substrate for producing pure hydrogen on-board due to the fact that it does not require desulfurization or pre-reforming processes [1]. Additionally, only minimal coke formation is obtained during the steam reforming of methanol (SRM) compared to that produced from the other substrates. However, the H2-rich stream is always contaminated with CO, although the CO concentration depends on the

* Corresponding author. Department of Chemical Technology, Faculty of Science, Chulalongkorn University, 254 Phayathai Road, Patumwan, Bangkok 10330, Thailand. Tel.: þ662 218 7676; fax: þ662 255 5831. E-mail addresses: [email protected], [email protected] (S. Pongstabodee). 0360-3199/$ e see front matter Copyright ª 2011, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.ijhydene.2011.12.023

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type of feedstock, operating procedure and the performance of the catalysts used in the hydrogen production unit. The CO elimination unit is required in the hydrogen-fuel processor system since even trace levels of CO show strong chemisorption on the anodic platinum (Pt) electrode of the PEMFC and lower its performance dramatically. The wateregas shift (WGS) reaction is then used to reduce the CO level from w3e10% (v/v) to w1% (v/v), while the preferential oxidation (PROX) of CO is further employed to clean-up the CO within acceptable levels (<10 ppm). Among the current methods in use for the CO elimination unit, the PROX of CO seems to be one of the most effective methods with an economic approach and minimal loss of H2. The main reaction is as follows: CO þ 1=2O2 /CO2

DH ¼ 283 kJ=mol

(1)

and the undesired side reactions are hydrogen oxidation (Eq. (2)), WGS reaction (Eq. (3)) and methanation (Eq. (4)): H2 þ 1=2O2 /H2 O CO þ H2 O/CO2 þH2 CO þ 3H2 /CH4 þH2 O

DH ¼ 241:8 kJ=mol DH ¼ 41:2 kJ=mol DH ¼ 206:1 kJ=mol

(2) (3) (4)

The catalysts for the PROX of CO should exhibit a high CO conversion including a high selectivity with respect to minimization of the undesired side reactions. Furthermore, the catalysts should be active in the presence of water and CO2 since they are some of the main components in the H2-rich stream from hydrogen production unit. Therefore, the development of catalysts with a suitable performance (rate, sensitivity and selectivity) for the PROX of CO in the realistic reformate gas is still needed. Catalysts are classified into the two major categories of noble [2e12] and non-noble catalysts [2,13e22]. The optimal catalytic activities of supported Pt catalysts are shifted to a higher temperature when CO2 [5,6] or water [5,7] or both [5,6] are present in the feedstream, although some reports have claimed that the supported Pt catalysts were not deactivated in the presence of CO2 and water [2,8]. Moreover, adding excess O2 in the H2-rich stream encourages not only a higher catalytic performance of the supported Pt catalysts but also a higher level of hydrogen consumption. Some research reports have highlighted a significant decrease in the catalytic activities of supported gold (Au) catalysts in the presence of CO2 alone [4,9] or in the presence of CO2 and water [2,3,9], whereas the presence of only a small amount of water enhanced the catalytic activity of the Au catalysts [3,4]. In our previous work [10], we studied catalytic performance of a series of PteAu catalysts prepared by co-precipitation (CP) and single step sol-gel methods (SSG) for selective CO oxidation. We found that the catalytic performance over PtAu/Ce1Zn1O2 prepared by coprecipitation was higher than that of PtAu/CeO2 and PtAu/ ZnO due to a higher metallic surface area and a smaller particle size. The catalytic activity of supported Au catalysts depends on the dispersion and size of the Au particles, the type of support material and the preparation method. Supported copper [2,13e19,21,22] and manganese [20] catalysts are effective for the PROX of CO but their activities are

decreased significantly in the presence of water and CO2. Therefore, the presence of either water, CO2 or both has a negative influence on the catalytic PROX of CO. However, it is important to note that these studies have been investigated on the assumption of no-interaction between the factors, called a univariate (one-variable-at-a-time) experimental approach. A statistical design of experiment (DOE) was employed in this work, since it is a powerful tool for process investigation and optimization [17,23e26], by simultaneously considering many factors at different levels and their potential interactions. Thus, the catalytic activity for the PROX of CO over a 1% (w/w) PtAu/CeO2eZnO catalyst was evaluated in terms of the CO conversion and selectivity with respect to the operating temperature (
C) and the presence of water (%) and CO2 (%) in the simulating methanol reformate gas. The importance of each factor and their interactions were evaluated by a full 23 factorial design. After screening the importance of each of the three factors and their interactions on the % CO conversion and selectivity, a face-centered central composite design (FCCCD) falling under response surface methodology (RSM) was then applied to optimize the responses. It is worth remarking that, after determining the optimization, the validation of the developed models was tested for both simulating reformate gas and realistic methanol reformate gas. In addition, the stability of the catalyst under realistic methanol reformate gas was evaluated over a continuous 10 h time period.

2.

Experimental

2.1.

Catalyst preparation

The 1% (w/w) PtAu/CeO2eZnO catalyst was prepared by coprecipitation. The desired amount of Ce(NO3)3$6H2O (Merck), (Merck), H2PtCl6$6H2O (Fluka) and Zn(NO3)2$4H2O HAuCl4$3H2O (Fluka) were mixed simultaneously to make an aqueous solution and stirred continuously. The mixed solution was held at pH 8 by the drop wise addition of 0.5 M Na2CO3 aqueous solution as required. The molar ratios of Pt to Au and of Ce to Zn were kept constant at 1:1. After aging for 1 h at 80
C, the precipitated material in suspension was harvested by filtration, washed with warm deionized water several times to remove the excess ions, dried at 110
C for 12 h and then calcined at 500
C for 5 h.

2.2.

Catalyst characterization

The particle morphology of the catalysts was observed by transmission electron microscopy (TEM) using a JEM 2010 TEM microscope operating at 200 kV in bright and dark field modes. The BrunauereEmmetteTeller (BET) method for evaluating the surface area of the catalyst was examined by N2 adsorption/desorption at 196
C (Micromeritics ASAP 2020). The crystalline structure was determined by X-ray diffractometry (XRD) using a Rigaku X-ray diffractometer system equipped with a RINT 2000 wide-angle goniometer and using CuKa ˚ ) and a power of 40 kV  30 mA. The radiation (l ¼ 1.54 A particle diameter was calculated by the DebyeeScherrer equation at the main X-ray line broadening in each phase.

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Fourier transform infrared spectrometry (FTIR) was used to investigate the functional groups. Solid sample was milled with potassium bromide (KBr) to form a very fine powder. The powder was then compressed into a thin pellet to be analyzed. The spectra were collected on a PerkineElmer (Spectrum one) spectrometer equipped with a mercury-cadmium-telluride (MCT) detector to record wavenumber range of functional group.

2.3.

Catalytic activity measurement

The catalytic activity for the PROX of CO over a 1% (w/w) PtAu/ CeO2eZnO catalyst was investigated at atmospheric pressure. A 100 mg catalyst sample was placed between two layers of quartz wool in the middle of a 6 mm ID fixed-bed U-tube reactor. The simulating reformate gas, which consisted of (all (v/v)) 1% CO, 1% O2, 0%e10% H2O, 0%e20% CO2 and 40% H2 with the remainder made up of He, was routed to the reactor at a flow rate of 50 cm3 min1 by a mass flow controller. The operating temperature was controlled in the range of 50
Ce190
C and monitored by a thermocouple placed in the center of the catalyst bed. The influent and effluent gases were routed to an ice-condenser to trap the water and then analyzed by on-line gas chromatograph (Agilent Technologies, model 6890N) equipped with a carbosphere column and a thermal conductivity detector (TCD). Helium was used as the carrier gas. The catalytic activities are expressed in terms of the % CO conversion and selectivity, which were calculated based on the CO consumption, as shown below: CO conversion ð%Þ ¼

CO selectivity ð%Þ ¼

½COin  ½COout  100 ½COin

(5)


0:5  ½COin  ½COout  100 ½O2 in  ½O2 out

(6)

where [CO]in and [CO]out are the concentrations of CO (% (v/v)) in the feedstream and the effluent, respectively, [O2]in and [O2]out are the concentrations of O2 (% (v/v)) in the feedstream and the effluent, respectively.

2.4.

Statistical design of experiments

2.4.1.

A full 2k factorial design

A factorial design was carried out to evaluate the effect of the operating temperature (
C), H2O content (% (v/v)) and CO2 content (% (v/v)) in the reformate gas, and their interactions on the catalytic activities for the PROX of CO in terms of the %

CO conversion and selectivity. The other factors that likely affect the catalytic activities, including the catalyst weight to total gas flow rate (W/F), catalyst type and the reactor volume were held constant throughout all the experiments. The experimental matrix for a full 23 factorial design with three central points was then designed and employed. The experiments were done in a completely random order in order to minimize errors due to systematic trends in the factors. The DesigneExpert 5.0 software package (Stat Ease Inc. Minneapolis, USA) was employed to treat the experimental data and to perform the statistical analysis at a 95% confidence interval, such as the normal probability of the residues, the Pareto chart of absolute standardized effect, analysis of variance (ANOVA) and the % contribution.

2.4.2.

Response surface methodology (RSM)

After screening the three factors and their interactions for any significant effect upon the CO conversion and selectivity with the factorial design (Section 2.4.1), the factors found to be important (significant influence) were then selected for RSM analysis. To this end, FCCCD with the above important factors was applied sequentially to optimize the conditions for the PROX of CO by simultaneously considering maximal CO conversion, selectivity, the composition of realistic reformate gas and temperature of the feedstream. A standard ANOVA at a 95% confidence interval was then carried out to analyze the response surface models.

2.4.3.

Validation of the model

The independent screened factors which were found to have the major influence on the CO conversion and selectivity (Section 2.4.1) were randomly selected within the given levels to investigate the accuracy of the developed model as obtained from the RSM (Section 2.4.2). The other less important factors were held constant at their respective optimal level. A set of six experiments were then designed and employed under a feed condition of simulating and realistic reformate gases. The residual distribution plot, a statistical analysis tool for determining the validity of the model, was then employed.

3.

Results and discussion

3.1.

Catalyst characterization

The physical properties of the fresh and spent 1% (w/w) PtAu/ CeO2eZnO catalysts are summarized in Table 1. No major or

Table 1 e Physical properties of the prepared catalysts. Catalyst

PtAu/CeO2eZnO PtAu/CeO2eZnO

Status

Fresh Spentc

BET surface areaa (m2 g1)

58.6 54.7

Pore volumea (cm3 g1)

0.16 0.15

Crystallite sizeb (nm) CeO2

ZnO

7.7 7.6

27.1 23.7

a Determined by BET surface analyzer. b Determined by XRD from the line broadening of CeO2 (1 1 1) and ZnO (1 0 1). c Composition of the realistic reformate gas (all (v/v)) was 36.8% H2, 1.1% CO, 1.1% O2, 8.2% H2O, 11.6% CO2 and 41.2% He.

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Fig. 1 e Representative TEM images and derived PteAu particle size distribution for the (a) fresh and (b) spent 1% (w/w) PtAu/ CeO2eZnO catalyst. The composition of the realistic reformate gas was (all (v/v)) 36.8% H2, 1.1% CO, 1.1% O2, 8.2% H2O, 11.6% CO2, and 41.2% He.

significant difference between the fresh and spent catalysts in their BET surface area, pore volume or the CeO2 and ZnO crystallite size were observed. The average particle size of catalyst and its size distribution were determined from the

(d) % Transmission

Cerianite Zincite

Intensity [cps]

(e)

(c) (b) (a)

(b)

1000

1500

2000

2500

3000

3500

4000

-1

Wavenumber (cm )

(a)

20

30

40

50

60

70

80

90

2Theta [degree]

Fig. 2 e Representative XRD patterns for the (a) fresh and (b) spent 1% (w/w) PtAu/CeO2eZnO catalyst. The composition of the realistic reformate gas was (all (v/v)) 36.8% H2, 1.1% CO, 1.1% O2, 8.2% H2O, 11.6% CO2 and 41.2% He.

Fig. 3 e Representative FTIR spectra for the (a) fresh 1% (w/ w) PtAu/CeO2eZnO catalyst and (bee) the spent catalyst with varying (bed) simulated or (e) realistic reformate gas compositions. The simulated reformate gas compositions were all (v/v) 40% H2, 1% CO and 1% O2, and then supplemented with (b) nothing, (c) 10% H2O or (d) 20% CO2. The realistic reformate gas composition was 36.8% H2, 1.1% CO and 1.1% O2, 8.2% H2O, 11.6% CO2. In all cases the remaining proportion of the gas was He.

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100

(a)

CO conversion (%) and selectivity (%)

90

(b)

(c)

(d)

80 70 60 50 40 30 20 10 190

170

150

130

90

110

70

190 50

170

150

130

90

110

70

190 50

170

150

130

90

110

190 50 70

170

150

130

90

110

70

50

0

Temperature (°C) Fig. 4 e The catalytic performance (solid line for conversion; dashed line for selectivity) of the 1% (w/w) PtAu/CeO2eZnO catalyst over the operating temperature range of 50e190
C when feeding the feedstream with (all (v/v)) 40% H2, 1% CO and 1% O2 supplemented with (a) nothing, (b) 10% H2O, (c) 20% CO2 and (d) 10% H2O and 20% CO2. In all cases the residual gas composition was He.

TEM images (Fig. 1) when routing realistic reformate gas as the feedstream. Black spots, which were dispersed throughout the area, are the bi-metallic phase of Pt and Au, which implies that the catalysts are well dispersed on the support, and individual Pt-metallic phases could not be separated from the Au-metallic phases. The mixed oxide support is visualized as the grey area. However, the average size of the fresh metallic particles was smaller, compared to that of the spent catalyst. The XRD patterns of the fresh and spent catalysts are displayed in Fig. 2, where all the peaks correspond to the mixed oxide support. There were no characteristic peaks of Pt (2q ¼ 39.8
and 46.2
) or Au (2q ¼ 38.2
, 44.4
and 77.6
), which suggests that the Pt and Au particles were highly dispersed on surface of the mixed oxide support and/or that the actual Pt or Au loading level (<1%) in the catalysts is too low to be detected. Alternatively, the bi-metallic phase (Pt and Au) particles could be too small to be detected by XRD. Regardless, these

results are consistent with the TEM images. The peaks at 28.6
, 33.2
, 47.5
, 56.3
, 59.1
, 69.4
, 76.7
, 79.1
and 88.4
correspond to the cerianite phase (CeO2), whereas the diffraction peaks at 31.8
, 34.6
, 36.2
, 62.9
and 68.0
are from the zincite phase (ZnO). The intensity peak of the fresh catalyst was higher than that of the spent ones, supporting that the fresh catalysts had a higher crystalline content when compared to the spent ones. The crystallite size of the metal oxide phases (CeO2, and ZnO), as calculated by the DebyeeScherrer equation from the X-ray line broadening of the (1 1 1) diffraction peak for CeO2 and the (1 0 1) diffraction peak for ZnO, are the same for the spent and fresh catalysts except that the peak intensity is larger in the fresh catalysts (Table 1; Fig. 2). The functional group(s) on the surface of the fresh and spent catalysts was evaluated by FTIR analysis, with an example of the obtained spectra shown in Fig. 3. The fresh catalyst showed an absorbance peak at around

Table 2 e Experimental matrix (full 23 factorial design with three central points) for, and the results of, the evaluation of the PROX of CO over a 1% (w/w) PtAu/CeO2eZnO catalyst. Factors A B C

Standard order 1 2 3 4 5 6 7 8 9 10 11

Variables

Unit

Low (1)

Medium (0)

High (1)

50 0 0

120 5 10

190 10 20




Temperature H2O content CO2 content

C % %

Run order

A

B

C

CO conversion (%)

CO selectivity (%)

9 10 6 3 11 2 1 4 5 7 8

1 1 1 1 1 1 1 1 0 0 0

1 1 1 1 1 1 1 1 0 0 0

1 1 1 1 1 1 1 1 0 0 0

25.7 47.5 22.6 53.6 7.91 42.0 6.92 45.2 87.2 83.1 83.9

70.0 20.9 70.5 25.0 66.6 19.9 66.0 21.3 37.1 33.0 40.0

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a

7.50

Curvature

55.67 1.28

ABC

BC 0.18 4.91

AC AB

3.38 11.82

C B

1.30

A

31.30 0

10

20

30

40

50

60

Standardized Effect

b

5.65

Curvature

8.72

ABC 0.41 BC

0.93

AC

0.80

AB

1.37 3.16

C B

1.35

A 0

Fig. 5 e Normal probability plot of the effects for a full 23 factorial design with three central points when using the % CO (a) conversion and (b) selectivity as the response.

3100e3700 cm1 with the center at w3500 cm1, which represents the OeH stretching mode [27,28]. The intensity of this OeH peak in the fresh catalyst is higher than that of the spent catalyst when no H2O was added to the feedstream. In addition, the spectra of the spent catalysts displayed absorbance bands in two further regions; 1200e1700 cm1 and 2852e2960 cm1. The vibrational stretching frequencies at 1200e1700 cm1 correspond to carbonate species, formed from chemisorption of CO2 on the catalyst surface [28,29]. The bands at 1520e1550 cm1 and 1360e1385 cm1 range represent the asymmetric and symmetric stretching of unidentate carbonate species, respectively. The bands at 1610e1640 cm1 are OeCeO asymmetric stretches of the bidentate carbonate species. The CeH stretching peak at 2852 and 2960 cm1 represents either formate [30] or methoxy groups [31]. These results agree with the work reported by Martı´nez-Arias et al. [32]. When H2O was added to the feedstream, the intensity of

46.52 10

20

30

40

50

60

Standardized Effect

Fig. 6 e The Pareto diagram for a full 23 factorial design with three central points when using the % CO (a) conversion and (b) selectivity as the response. The absolute standardized value of the effect of each factor and its interaction appear at the right of each bar.

the OeH peak in the spent catalyst was higher than that of the fresh one (Fig. 3a and c), whilst the addition of CO2 (Fig. 3d) or the co-addition of H2O and CO2 (Fig. 3e) to the feedstream resulted in a broadened band for the OeH peak and a higher intensity of the carbonateetype and formate peaks compared to that seen in the fresh catalyst (Fig. 3a).

3.2.

Catalyst activities

The catalytic activity of the 1% (w/w) PtAu/CeO2eZnO catalyst, in terms of the % CO conversion and selectivity, at an operating temperature range of 50
Ce190
C when routing the

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Table 3 e ANOVA results of the % CO conversion and selectivity data obtained from the full 23 factorial design with three central points for the PROX of CO over a 1% (w/w) PtAu/CeO2eZnO catalyst. Source

Sum of squares

DFa

Mean square

F-value

Probability (P-value)

Contribution (%)

7 1 1 1 1 1 1 1 1 2 10

331.01 1959.69 3.37 279.54 22.88 48.27 0.067 3.26 6197.43 4.81

68.87 407.73 0.70 58.16 4.76 10.04 0.014 0.68 1289.41

0.0024 0.4907 0.0168 0.1608 0.0868 0.9170 0.4965 0.008

22.99 0.04 3.28 0.27 0.57 0.0007 0.04 72.70 0.11

7 1 1 1 1 1 1 1 1 2 10

622.68 4327.29 3.62 20.03 3.78 1.30 1.71 0.34 152.03 12.27

50.73 352.64 0.29 1.63 0.31 0.11 0.14 0.028 12.39

0.0028 0.6416 0.3296 0.6346 0.7760 0.7447 0.8824 0.0421

95.43 0.08 0.44 0.08 0.03 0.04 0.01 3.35 0.54

b

(a) Response: % CO conversion Model 2317.08 A 1959.69 B 3.37 C 279.54 AB 22.88 AC 48.27 BC 0.067 ABC 3.26 Curvature 6197.43 Residual 9.61 Cor Total 8524.13 (b) Response: % CO selectivityc Model 4358.08 A 4327.29 B 3.62 C 20.03 AB 3.78 AC 1.30 BC 1.71 ABC 0.34 Curvature 152.03 Residual 24.54 Cor Total 4534.65

a DF ¼ Degrees of freedom. A, B and C are as defined in Table 2. b R-Squared ¼ 0.9959 and Adj. R-Squared ¼ 0.9814. c R-Squared ¼ 0.9944 and Adj. R-Squared ¼ 0.9748.

feedstream with various compositions are presented in Fig. 4. The catalytic performance decreased with any further increase in the operating temperature after achieving the maximum % CO conversion, but the temperature required to attain the maximum % CO conversion changed with the different feedstream gas compositions. Without the addition of H2O and/or CO2 to the feedstream (Fig. 4a) the % CO conversion increased 3.72-fold from w25%ew93% as the temperature increased from 50
C to the optimal at 90
C. Here, CO reacted with O2 to produce CO2 which could then be chemisorbed on the catalyst surface as carbonate, as evidenced in FTIR spectra (see Fig. 3b). Further increasing the temperature from 90
C to 190
C significantly (1.98-fold) decreased the % CO conversion to w47% because of the competition of the undesired reaction of H2 oxidation. The obvious evidence for that is provided by catalytic activity results themselves, the OeH intensity increase providing only indirect support that H2O has been formed (see Fig. 3b). CO selectivity was decreased when increasing the operating temperature. Overall, a w93% of the maximum %CO conversion with w41% of its selectivity was achieved at 90
C. When 10% (v/v) H2O was added to the feedstream a similar trend of results were seen to that obtained without H2O and CO2. And discussed above, with an optimal % CO conversion at 90
C and declining thereafter with increasing temperature, but not as sharply as that seen without water. That is with the addition of 10% (v/v) H2O to the feedstream, the % CO conversion was some 5%e10% higher at each respective operating temperature of >90
C than that seen without the addition of water. The presence of H2O in the feedstream thus

increases the catalytic activity for CO oxidation. Indeed, as evidenced from the FTIR analysis, the spent catalyst from the reaction with added H2O to the feedstream (Fig. 3c) showed a higher intensity peak of the hydroxyl group and a lower intensity of the carbonate and formate vibrational stretching peaks compared to that seen without the addition of H2O and CO2 (Fig. 3b). The slight positive effect of the presence of H2O on the catalytic activity is likely to be due to the provision of hydroxyl groups from the water for the CO oxidation reaction to take place, and so results in a shift in the % CO conversion. When adding H2O to the feedstream, a lower accumulation of the carbonate intermediate and formate species on the catalyst surface was observed even though the % CO conversion was enhanced, which indicates that water may have attacked and decomposed some of the carbonate intermediate on the catalyst surface. The addition of CO2 in the feedstream caused a dramatic decrease in the maximum % CO conversion and selectivity (Fig. 4c), with only a w56% conversion and w28% selectivity compared to that seen without the addition of CO2 and H2O in feedstream. The operating temperature for the maximal % CO conversion was shifted from 90
C to 150
C. These results are in agreement with those reported by Schubert et al. [4] and Panzera et al. [33], where the presence of CO2 also significantly increased the maximum conversion temperature. This dramatic decrease in the catalytic performance was likely to be due to CO2 chemisorption that results in the formation of carbonate intermediates and formate species on the catalyst surface, as evidenced in the FTIR spectra (Fig. 3d). The accumulation of these species on the catalyst surface could block

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Fig. 7 e Main effect plot with its response for the % CO (a) conversion and (b) selectivity.

the active sites for the PROX of CO. Thus, the presence of CO2 in the feedstream has a significant negative effect on the performance of the catalyst. The co-addition of 10% (v/v) H2O and 20% (v/v) CO2 to the feedstream was somewhat intermediate between that seen with the addition of either 10% (v/v) H2O or 20% (v/v) CO2 alone, but potentially biased more toward that of 20% (v/v) CO2. From Fig. 4d, the % CO conversion profile was much lower than that obtained without the co-addition of CO2 and H2O, or the addition of 10% (v/v) H2O, to the feedstream but was only slightly higher than that seen with the addition of 20% (v/v) CO2 to the feedstream. It thus appears that the negative affect of the addition of 20% (v/v) CO2 upon the % CO conversion by the catalyst is greater then the positive effect of the addition of 10% (v/v) H2O, although this requires further counter-titrations for confirmation. The maximum % CO conversion and selectivity, obtained at 130
C, was around w63% and w30%, respectively. The operating temperature for the maximal % CO conversion was shifted lower compared to that seen with the addition of CO2 (150
C), as has been reported before [3e6,9,19,20,22]. Comparing the FTIR spectra (Fig. 3dee) suggests that a lower

level of formation of the carbonate intermediate and formate species on the catalyst surface occurred when co-adding H2O and CO2 to the feedstream than when adding only CO2. It is, however, surprising that a higher intensity of the hydroxyl region was observed compared to when adding only CO2 to the feedstream. The lower negative effect of the co-addition of H2O and CO2 to the feedstream on the catalytic activities compared to that for the addition of CO2 only can probably be explained by the fact that water can provide hydroxyl groups where the reaction takes place. Carbonate intermediate on the catalyst surface may be attacked and decomposed by water [34], and results in a reduced accumulation of the formate species on the active sites of the catalyst.

3.3.

Factors screening in a full 23 factorial design

Based on the catalytic activities for the PROX of CO, the importance of the three independent factors (Section 3.2) on the catalytic activity was evaluated by using a full 23 factorial design with three central points and using the % CO conversion and selectivity as responses. The factor levels on the

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Table 4 e Experimental variables for a faced-centered central composite design (FCCCD) response surface methodology (RSM) with three central points for the PROX of CO over a 1% (w/w) PtAu/CeO2eZnO catalyst. Factors A C

Standard order

Variables Temperature CO2 content

Unit

Low (1)

Medium (0)

High (1)

90 0

120 10

150 20




C %

Run order

A

C

CO conversion (%)

CO selectivity (%)

9 2 8 10 5 1 4 3 7 11 6

90 150 90 150 90 150 120 120 120 120 120

0 0 20 20 10 10 0 20 10 10 10

93.0 67.9 16.3 56.1 54.7 62.0 80.3 38.6 59.4 58.2 57.2

41.0 30.0 59.9 28.2 50.5 29.1 35.4 44.6 37.1 40.0 40.0

1 2 3 4 5 6 7 8 9 10 11

Note: The H2O content in the feedstream was held at the medium level (5% (v/v)), as given in the factorial design (Table 2).

natural scale were encoded in the dimensionless scale as þ1 for the high level, 0 for the central point and 1 for the low level, as shown in the upper section of Table 2. The statistically designed set of experimental matrix and the responses are presented in the lower section of Table 2. A normal probability plot of the effect estimates was then constructed in order to evaluate each independent factor and its interactions for both the % CO conversion and selectivity (Fig. 5). Based on the zero value of the abscissa at a 50% normal probability level, these graphs could be divided in two regions, one of a positive influence and the other of a negative influence on the response, each with a normal probability of less than 50%. The factors and interactions that were positioned outside of the normal probability line are those that have a significant influence on the response. With respect to the % CO conversion (Fig. 5a), the H2O content in

the feedstream and the interactions between all three factors had no significant influence on the response at the 95% confidence interval. Only the operating temperature and CO2 content in feedstream had a significant effect on the % CO conversion, being positive for the operating temperature and negative for the CO2 content, respectively. For the % CO selectivity, only the operating temperature had a significant negative effect on the % CO selectivity, giving a lower CO selectivity with increasing temperature. This statistical analysis is consistent with the observed experimental activity measurements (see Fig. 4). The Pareto chart (Fig. 6) displays the absolute standardized effect at a 95% confidence interval for both the % CO conversion and selectivity responses. With respect to the % CO conversion response, only the operating temperature and CO2 content in the feedstream expressed an absolute value higher

Table 5 e ANOVA results of the % CO conversion and selectivity data derived from the FCCCD RSM for the PROX of CO over a 1% (w/w) PtAu/CeO2eZnO catalyst. Source

Sum of squares

DFa

Mean square

F-value

Probability (P-value)

3 1 1 1 5 2 10

1319.95 81.18 2825.34 1053.33 0.88 1.19

1359.42 83.61 2909.82 1084.82 0.74

<0.0001 <0.0001 <0.0001 0.6604

3 1 1 1 5 2 10

303.07 686.94 115.37 106.92 0.32 2.74

300.10 680.19 114.24 105.86 0.12

<0.0001 <0.0001 <0.0001 0.9757

b

(a) Response: % CO conversion Model 3959.85 A 81.18 C 2825.34 AC 1053.33 Lack of fit 4.41 Residual 2.38 Cor Total 3966.64 (b) Response: % CO selectivityc Model 909.22 A 686.94 C 115.37 AC 106.92 Lack of fit 1.60 Residual 5.47 Cor total 916.29

a DF ¼ Degrees of freedom. A and C are as defined in Table 2. b R-Squared ¼ 0.9983, Adj. R-Squared ¼ 0.9976 and Adeq. Precision ¼ 127.66. c R-Squared ¼ 0.9923, Adj. R-Squared ¼ 0.9890 and Adeq. Precision ¼ 52.38.

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54.56

20

49.27

43.98

38.69

33.40

29.55

C : C O 2 content

15

42.20 54.84

10

67.48 5

80.12 0 90

105

120

135

150

A: Temperature

Fig. 8 e Contour plot of the RSM model derived % CO ( ) ) selectivity and (shaded portion) the conversion and ( optimal region. The plot was formed by overlaying the yield of the w% CO conversion and selectivity responses, the CO2 content in the realistic reformate gas and the temperature of the feedstream.

than 7.50, and so had a significant influence on the % CO conversion. For the % CO selectivity, only the operating temperature had an absolute standardized value higher than 5.65, and so had a significant influence on the CO selectivity. These results were also confirmed by a normal probability plot of the effect estimates. Moreover, an appearance of curvature was observed in the % CO conversion and selectivity responses. The absolute value of curvature was around 55.67 (7.43-fold) and 8.72 (1.54-fold) for the % CO conversion and selectivity responses, respectively. However, it is surprising that the addition of H2O in the feedstream had no significant

effect on the % CO conversion and selectivity responses at the 95% confidence interval. The ANOVA of the catalytic performance is shown in Table 3. For the % CO conversion response, only the operating temperature and CO2 content in the feedstream were significant, their relative importance (% contribution) being w23.0% and 3.28% for the operating temperature and CO2 content in the feedstream, respectively. With respect to the % CO selectivity response, only the operating temperature was an important factor with a 95.43% contribution. In addition, the relationship between the important factors and the response was not linear, since the probability of a curvature was P ¼ 0.008 and 0.0421 (72.7% and 3.35% contribution) for the % CO conversion and selectivity responses, respectively. The magnitude of the adjusted-R2 (Adj R-square) term was close to the coefficient of determination (R-square), which implies that non-significant terms have been included in the models [26,35] for CO conversion and selectivity. In order to verify the curvature, the mean changes that occurred in the response when changing the level of the factor from a lower level through the central point to a higher level were plotted (Fig. 7). The average of the response value for all three factors studied did not correspond to the average of the response value at the central point, which suggested that there should be a quadratic term in the % CO conversion and selectivity models. From the results of statistical analysis, it can be concluded that an operating temperature and CO2 content in feedstream have a significant effect on the CO conversion whist only operating temperature has an influence on CO selectivity. Therefore, the operating temperature and CO2 content in feedstream were employed for a surface analysis design in order to achieve an optimal CO conversion and CO selectivity.

3.4.

Response surface methodology (RSM)

After screening for the important factor(s) that influence the % CO conversion and selectivity responses using a full 23

Table 6 e Validation of FCCCD using various operating temperatures and CO2 contents when feeding (a) simulated and (b) realistic reformate gas. Operating condition


Temperature ( C) (a) Simulated reformate gas 90 120 130 150 150 170 (b) Realistic reformate gas 100 110 120 130 140 150

CO conversion (%) CO2 content (%)

CO selectivity (%)

Estimation

Experiment

Estimation

Experiment

10 10 0 0 20 0

54.8 58.5 76.0 67.7 56.7 59.3

54.7 59.4 76.4 67.9 56.1 58.3

50.3 39.6 33.4 29.7 28.1 26.0

50.5 40.0 33.7 30.0 28.2 25.7

11.6 11.6 11.6 11.6 11.6 11.6

50.9 53.0 55.1 57.1 59.2 61.3

49.4 53.7 56.3 56.3 60.0 62.4

48.0 44.1 40.3 36.6 32.6 28.8

46.9 45.2 39.9 35.7 33.2 28.4

Note: The simulated reformate gas consisted of (all (v/v)) 40% H2, 1% CO, 1% O2, 5% H2O, the indicated amount of CO2 (shown in Table) and the rest as He, whilst the realistic reformate gas composition from the SRM unit consisted of (all (v/v)) 36.8% H2, 1.1% CO, 1.1% O2, 8.2% H2O, 11.6% CO2 and 41.2% He.

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CO conversion ð%Þ ¼ þ58:52 þ 3:68A  21:70C þ 16:23AC

(7)

CO selectivity ð%Þ ¼ þ39:60  10:70A þ 4:38C  5:17AC

(8)

a

5 4 3 2

Residual (%)

factorial design with central points, a FCCCD with two independent screened factors was performed in order to achieve the optimum condition for CO conversion and selectivity. The criterion of this design and the level of the screened factors were chosen based on the previous full 23 factorial design (Section 3.3), as shown in Table 4. Based on the components of the realistic reformate gas from the SRM unit, the statistical analysis and catalytic activities, the H2O content in the feedstream was held constant at a medium level. An appropriate RSM model was generated in coded terms, as shown in Eq. (7) for the % CO conversion and Eq. (8) for the % selectivity responses:

1 0 -1 -2 -3 -4 -5 0

10

20

30

40

50

60

70

80

90

100

70

80

90

100

Predicted value (%)

b

5 4 3 2

Residual (%)

where A is the operating temperature (
C), C is the CO2 content in the feedstream (% (v/v)) and AC is the interaction between the operating temperature and the CO2 content in the feedstream. The conditions that yielded the optimal CO selectivity (59.9%), at 90
C and 20% (v/v) CO2, however, yielded the lowest % CO conversion (16.3%). Conditions that then lead to an improved % CO conversion typically yield a reduced % CO selectivity, but not in a linear manner. Thus, the optimization of conditions for both % CO conversion and selectivity is discussed below using overlay plots. ANOVA analysis of the FCCCD results revealed that both the temperature and the CO2 content and their interaction were a significant influence on the % CO conversion and selectivity (Table 5). Note that the lack of fit in the developed models was not significant, implying that the independent factors studied were adequate to represent the actual relationship between these two factors and the responses within the selected range. The R-Squared value provides a variability measurement in the estimated response value when using the factors and their interaction. The Adj R-Squared values of 0.9976 and 0.9890 for the % CO conversion and selectivity response, respectively, being very close to 1 revealed the accuracy of the response surface quadratic model [36,37]. Indeed, only 0.24% and 1.1% of the total variation in the % CO conversion and selectivity responses, respectively, could not be explained by the models. Accordingly, there was very little difference between the R-Squared and Adj R-Squared values. When monitoring the signal to noise ratio by adequate precision (Adeq Precision), it has been suggested that the signal is adequate when the ratio was greater than 4. Here the signal to noise ratio for the % CO conversion and selectivity were 127.66 and 52.38, respectively, and so displayed an adequate model perception, and explained the good agreement between the estimated and experimental response values for both the CO conversion and selectivity. A relatively straightforward approach to optimizing the counter trending CO conversion and selectivity (Table 4) is to overlay the contour plot for each response, as shown in Fig. 8. To achieve the optimal condition, the CO2 content in the realistic reformate gas (9%e12%) and temperature of the feedstream (w100
Cew120
C) were also used as constraints for optimizing the responses. The optimal condition, which was estimated by simultaneously considering the CO conversion and selectivity responses and constraints, is in the

1 0 -1 -2 -3 -4 -5 0

10

20

30

40

50

60

Predicted value (%) Fig. 9 e Residual plots of the response surface model for the % CO (a) conversion and (b) selectivity when routing ( ) simulated and ( ) realistic reformate gases.

operating temperature range of w100
Cew115
C and a CO2 content of 9%e11% (v/v) in the feedstream (shaded portion of Fig. 8). Under these optimal conditions the maximal CO conversion and selectivity were in the range of w55%ew61% and w44%ew48%, respectively, which are in good agreement with the experimental results.

3.5.

Validation of the RSM models

To investigate the accuracy of the above RSM models (Section 3.4), the effect of the operating temperature and CO2 content in the feedstream were experimentally varied, whilst the H2O content in the simulated reformate gas was held constant at 5% (v/v). Table 6 shows the % CO conversion and selectivity of an individual representative experiment along with the estimated responses under the simulated and realistic reformate

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100

CO conversion (%) and selectivity (%)

90 80 70 60 50 40 30 20 10

CO conversion CO selectivity

0 0

50

100

150

200

250

300

350

400

450

500

550

600

Time (min)

Fig. 10 e Stability test of the PROX of CO unit over a 1% (w/ w) PtAu/CeO2eZnO catalyst under realistic SRM conditions (36.8% H2, 1.1% CO, 1.1% O2, 8.2% H2O, 11.6% CO2, and 41.2% He, all (v/v)) at the optimum condition (obtained from statistical analysis). (PROX unit condition: operating temperature [ 120
C). gases. The realistic reformate gas composition from the SRM unit was comprised of (all (v/v)) 36.8% H2, 1.1% CO, 1.1% O2, 8.2% H2O, 11.6% CO2 and 41.2% He. The realistic reformate gas was routed directly from the SRM unit to the PROX of CO unit. The estimated responses were found to be very close to the experimentally derived ones in all cases. Indeed, when the difference in the estimated and experimental response values, in terms of their % residuals, were plotted against the predicted value, the distribution of the residuals with regard to the response does not follow a trend for either response (Fig. 9). For the simulated and realistic reformate gases, all the residuals were within 2% and 3%, respectively, for both the CO conversion and selectivity responses, indicating a high degree of accuracy for the models. Since the RSM analysis provided an adequate approximation of the true response function, and so the analysis is approximately equivalent to analysis of the actual system, then the experimental design in this work can be applied to optimize the CO conversion and selectivity over a 1% (w/w) PtAu/CeO2eZnO catalyst.

3.6.

Stability test

The stability test of the PROX of CO unit under the realistic condition was performed at an operating temperature of 120
C (detailed in Fig. 10). The catalytic activity of the 1% (w/ w) PtAu/CeO2eZnO catalyst was found to be stable at this operating condition for 10 h, with no significant difference being observed in the % CO conversion or selectivity between the fresh and spent catalysts (Figs. 1 and 2; Table 1).

4.

Conclusions

The effects of the operating temperature (
C) and the H2O and CO2 contents (%) in the simulated reformate gas on the

catalytic performance for the preferential oxidation of CO over a 1% (w/w) PtAu/CeO2eZnO catalyst that was prepared by coprecipitation was investigated. The % CO conversion profile from the co-addition of 10% (v/v) H2O and 20% (v/v) CO2 was much lower than that obtained without the co-addition of CO2 and H2O or the addition of 10% (v/v) H2O to the feedstream but was only slightly higher than that seen with the addition of 20% (v/v) CO2 to the feedstream. As evidenced from the FTIR spectra, a lower level of formation of the carbonate intermediate and formate species with a higher intensity of the hydroxyl region on the catalyst surface occurred when coadding H2O and CO2 to the feedstream than when adding only CO2. For screening the importance of these factors on the catalytic activity, a full 23 factorial design with three central points was applied. Statistical analysis at a 95% confidence interval revealed that the operating temperature and CO2 content in the feedstream had a significant influence on the CO conversion response, whilst only the operating temperature was significant for the CO selectivity. However, a curvature was observed, which suggests a quadratic term in the models of the CO conversion and selectivity responses is required. Therefore, variation of the two important factors (temperature and CO2 content) and FCCCD with three central points were performed to evaluate the optimal condition by the simultaneous consideration of the maximal % CO conversion and selectivity, the constraint of the CO2 content in the realistic reformate gas (9e12% (v/v)) and temperature of the feedstream (w100e120
C). The optimal condition was found to be at w100e115
C and 9e11% CO2 content in the feedstream, yielding a maximal CO conversion and selectivity of w55e61% and w44e48%, respectively. The difference in the estimated and the experimental response was within 2% and 3% for routing the simulated and realistic reformate gas, respectively. No decrease in the catalyst performance was observed over a 10 h test period. The physical properties of the fresh catalysts were not different from the spent one. The experimental design in this work can be applied to optimize the CO conversion and selectivity over PtAu/CeO2eZnO catalysts.

Acknowledgments The authors are grateful to the Center for Petroleum, Petrochemicals and Advanced Materials, Chulalongkorn University, the National Research University Project of CHE, the Ratchadaphiseksomphot Endowment Fund (Project code: EN276B), the Department of Chemical Technology and The Petroleum and Petrochemical College, Chulalongkorn University, Thailand, for financial support.

references

[1] Brown LF. Comparative study of fuels for on-board hydrogen production for fuel-cell-powered automobiles. Int J Hydrogen Energy 2001;26:381e97. [2] Avgouropoulos G, Ioannides T, Papadopoulou Ch, Batista J, Hocevar S, Matralis HK. A comparative study of Pt/g-Al2O3,

i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 3 7 ( 2 0 1 2 ) 4 7 4 9 e4 7 6 1

[3]

[4]

[5]

[6]

[7]

[8]

[9]

[10]

[11]

[12]

[13]

[14]

[15]

[16]

[17]

[18]

[19]

Au/a-Fe2O3 and CuOeCeO2 catalysts for the selective oxidation of carbon monoxide in excess hydrogen. Catal Today 2002;75:157e67. Luengnaruemitchai A, Osuwan S, Gulari E. Selective catalytic oxidation of CO in the presence of H2 over gold catalyst. Int J Hydrogen Energy 2004;29:429e35. Schubert MM, Venugopal A, Kahlich MJ, Plzak V, Behm RJ. Influence of H2O and CO2 on the selective CO oxidation in H2rich gases over Au/a-Fe2O3. J Catal 2004;222:32e40. Ayastuy JL, Gil-Rodrı´guez A, Gonza´lez-Marcos MP, Gutie´rrezOrtiz MA. Effect of process variables on Pt/CeO2 catalyst behaviour for the PROX reaction. Int J Hydrogen Energy 2006; 31:2231e42. Zhou S, Yuan Z, Wang S. Selective CO oxidation with real methanol reformate over monolithic Pt group catalysts: PEMFC applications. Int J Hydrogen Energy 2006;31:924e33. Ko E-Y, Park ED, Seo KW, Lee HC, Lee D, Kim S. A comparative study of catalysts for the preferential CO oxidation in excess hydrogen. Catal Today 2006;116:377e83. ¨ zkara S‚, Aksoylu AE, O ¨ nsan ZI. Preferential CO S‚ims‚ek E, O oxidation over activated carbon supported catalysts in H2rich gas streams containing CO2 and H2O. Appl Catal A 2007; 316:169e74. Naknam P, Luengnaruemitchai A, Wongkasemjit S. Preferential CO oxidation over Au/ZnO and Au/ZnOeFe2O3 catalysts prepared by photo-deposition. Int J Hydrogen Energy 2009;34:9838e46. Monyanon S, Luengnaruemitchai A, Pongstabodee S. Preferential oxidation of carbon monoxide in simulated reformatted gas over PtAu/CexZnyO2 catalysts. Int J Hydrogen Energy 2010;35:3234e42. Monyanon S, Pongstabodee S, Luengnaruemitchai A. Preferential oxidation of carbon monoxide over Pt, Au monometallic catalyst, and PteAu bimetallic catalyst supported on ceria in hydrogen-rich reformate. J Chin Inst Chem Eng 2007;38:435e41. Parinyaswan A, Pongstabodee S, Luengnaruemitchai A. Catalytic performances of PtePd/CeO2 catalysts for selective CO oxidation. Int J Hydrogen Energy 2006;31:1942e9. Avgouropoulos G, Ioannides T. Selective CO oxidation over CuOeCeO2 catalysts prepared via the ureaenitrate combustion method. Appl Catal A 2003;244:155e67. Ratnasamy P, Srinivas D, Satyanarayana CVV, Manikandan P, Kumaran SRS, Sachin M, et al. Influence of the support on the preferential oxidation of CO in hydrogenrich steam reformates over the CuOeCeO2eZrO2 system. J Catal 2004;221:455e65. Park JW, Jeong JH, Yoon WL, Kim CS, Lee DK, Park Y-K, et al. Selective oxidation of CO in hydrogen-rich stream over CueCe catalyst promoted with transition metals. Int J Hydrogen Energy 2005;30:209e20. Chen Y-Z, Liaw B-J, Chang W-C, Huang C-T. Selective oxidation of CO in excess hydrogen over CuO/ CexZr1xO2.Al2O3 catalysts. Int J Hydrogen Energy 2007;32: 4550e8. Sirichaiprasert K, Ponstabodee S, Luengnaruemitchai A. Single- and double-stage catalytic preferential CO oxidation in H2-rich stream over an a-Fe2O3-promoted CuOeCeO2 catalyst. J Chin Inst Chem Eng 2008;39:597e607. Ramaswamy V, Malwadkar S, Chilukuri S. CueCe mixed oxides supported on Al-pillared clay: effect of method of preparation on catalytic activity in the preferential oxidation of carbon monoxide. Appl Catal B 2008;84:21e9. Chen Y-Z, Liaw B-J, Wang J-M, Huang C-T. Selective removal of CO from hydrogen-rich stream over CuO/CexSn1-xO2eAl2O3 catalysts. Int J Hydrogen Energy 2008;33:2389e99.

4761

[20] Guo Q, Liu Y. MnOx modified Co3O4-CeO2 catalysts for the preferential oxidation of CO in H2-rich gases. Appl Catal B 2008;82:19e26. [21] Gamarra D, Martı´nez-Arias A. Preferential oxidation of CO in rich H2 over CuO/CeO2: Operando-DRIFTS analysis of deactivating effect of CO2 and H2O. J Catal 2009;263:189e95. [22] Wu Z, Zhu H, Qin Z, Wang H, Ding J, Huang L, et al. CO preferential oxidation in H2-rich stream over a CuO/CeO2 catalyst with high H2O and CO2 tolerance. Fuel; 2010. doi:10.1016/j.fuel.2010.03.001. [23] Erickson PA, Liao C. Statistical validation and an empirical model of hydrogen production enhancement found by utilizing passive flow disturbance in the steam-reformation process. Exp Therm Fluid Sci 2007;32:467e74. [24] Hajjaji N, Renaudin V, Houas A, Pons MN. Factorial design of experiment (DOE) for parametric exergetic investigation of a steam methane reforming process for hydrogen production. Chem Eng Process 2010;49:500e7. [25] Thouchprasitchai N, Luengnaruemitchai A, Pongstabodee S. Statistical optimization by response surface methodology for wateregas shift reaction in a H2-rich stream over CueZneFe composite-oxide catalysts. J Taiwan Inst Chem Eng 2011;42: 632e9. [26] Montgomery DC. Design and analysis of experiments. 7th ed. U.S.A: John Wiley & Sons, Inc.; 2009. [27] Zaki MI, Hasan MA, Al-Sagheer FA, Pasupulety L. In situ FTIR spectra of pyridine adsorbed on SiO2eAl2O3, TiO2, ZrO2 and CeO2: general considerations for the identification of acid sites on surfaces of finely divided metal oxides. Colloids Surf A 2001;190:261e74. [28] Chowdhury A, Thompson PR, Milne SJ. TGAeFTIR study of a lead zirconate titanate gel made from a triol-based solegel system. Thermochimica Acta 2008;475:59e64. [29] Liao L-F, Lien C-F, Shieh D-L, Chen M-T, Lin J-L. FTIR study of adsorption and photoassisted oxygen isotopic exchange of carbon monoxide, carbon dioxide, carbonate, and formate on TiO2. J Phys Chem B 2002;106:11240e5. [30] Boccuzzi F, Chiorino A, Manzoli M. FTIR study of methanol decomposition on gold catalyst for fuel cells. J Power Sources 2003;118:304e10. [31] Larrubia Vargas MA, Busca G, Costantino U, Marmottini F, Montanari T, Patrono P, et al. An IR study of methanol steam reforming over ex-hydrotalcite CueZneAl catalysts. J Mol Catal A 2007;266:188e97. [32] Martı´nez-Arias A, Hungrı´a AB, Ferna´ndez-Garcı´a M, Conesa JC, Munuera G. Preferential oxidation of CO in a H2rich stream over CuO/CeO2 and CuO/(Ce, M)Ox (M ¼ Zr, Tb) catalysts. J Power Sources 2005;151:32e42. [33] Panzera G, Modafferi V, Candamano S, Donato A, Frusteri F, Antonucci PL. CO selective oxidation on ceria-supported Au catalysts for fuel cell application. J Power Sources 2004;135: 177e83. [34] Date´ M, Okumura M, Tsubota S, Haruta M. Statistical optimization of key process variables for enhanced hydrogen production by newly isolated Clostridium tyrobutyricum JM1. Angew Chem Int Ed 2004;43:2129e32. [35] Vining G, Kowalski SM. Statistical methods for engineers. 3rd ed. U.S.A: Brooks/Cole Cengage Learning; 2011. [36] Jo JH, Lee DS, Park D, Park JM. Statistical optimization of key process variables for enhanced hydrogen production by newly isolated Clostridium tyrobutyricum JM1. Int J Hydrogen Energy 2008;33:5176e83. [37] Long C, Cui J, Liu Z, Liu Y, Long M, Hua Z. Statistical optimization of fermentative hydrogen production from xylose by newly isolated Enterobacter sp. CN1. Int J Hydrogen Energy 2010;35:6657e64.